Machine Learning Operations Engineer I
Core
Build and support a mature ML platform, providing tooling and infrastructure to enable ML engineers to iterate quickly and ship robust production models and agentic applications.
Role type
MLOps Engineer I (IC)
Builds
Internal tooling, services, and frameworks for the ML workflow, model fine-tuning, reinforcement learning, and LLM/Agent evaluation pipelines.
Domain
Financial services / Generative AI / MLOps
Deliverable
production ML models
Required skills
Kubernetes, Python, AWS (EKS, Bedrock, SageMaker), distributed computing (Ray), workflow orchestration (Airflow), observability (Prometheus, W&B), Terraform, Bash, debugging distributed systems
Preferred skills
Agentic AI systems, MCP server patterns, Eval pipelines, LangGraph, PyTorch, Jsonnet, LangFuse, Sentry, open-source contribution
Technologies
Kubernetes, AWS, EKS, Bedrock, SageMaker, Ray, Airflow, Terraform, Python, Bash, LangGraph, PyTorch, Jsonnet, LangFuse, Sentry, Prometheus, W&B
Responsibilities
Iterate on ML processes to develop robust, auditable tools and services; Evaluate and champion open-source solutions for the platform ecosystem; Ship automated processes for model fine-tuning, RL, and LLM evaluation; Improve observability to detect performance decay and drift in agentic applications; Debug distributed systems across infrastructure and application layers.
Seniority
Junior to Mid-level, hands-on IC
